The present invention relates to battery control in a vehicle, and more particularly in determining equivalent circuit model parameters for modeling of a battery circuit when estimating battery power capability.
When employing batteries to provide power for some systems, such as for example a battery electric or hybrid electric vehicle, an estimation of the battery power capability may be estimated by a battery equivalent circuit model. In addition, the determination of the circuit model parameters may be calculated using an optimal data fitting process, which may employ, for example, an extended Kalman filter (EKF). A concern with employing an EKF approach is that the estimated values for the parameters are based on data fitting from measurement data. This can lead to model mismatch, as well as being corrupted by sensor biases or measurement noises in the measurement data. This may result in biased estimation of the parameters. For example, such modeling bias can lead to an electrical resistance being modeled as negative, which is physically impossible.
A possible approach is to use all possible ranges of equivalent battery model parameters to decide the limits (bounds) of circuit model parameters. However, with this approach the range for the circuit model parameters may be much larger than desirable. For example, for a modeled resistance of the battery equivalent circuit model, the lower and upper bound may be very large relative to how large the variation can actually be.
Thus, a way to employ an equivalent circuit model to estimate battery power capability, while minimizing/correcting errors in the battery circuit model parameters is desired.